Role : Senior AI Engineer, Agentic Systems (Java, Python) -15+ Years
Location : Plano, TX (5 days onsite in a week)
Long Term contract
JD: Position Summary
The Senior AI Engineer, Agentic Systems will design, build, deploy, and operate production-grade agentic AI systems that support enterprise-scale use cases. The role emphasizes shipped production experience, system reliability, orchestration, monitoring, debugging, and the ability to expose enterprise capabilities as tools or skills for LLM-powered agents.
Core Responsibilities
Build and operate production agentic AI systems, including deployed, monitored, and debugged agents running at scale.
Own agentic use cases end-to-end, partnering directly with business stakeholders from problem definition through delivery and operational support.
Design orchestration patterns for autonomous or semi-autonomous agents using modern agent frameworks and production orchestration layers.
Develop enterprise capabilities as tools or skills for LLMs, enabling agents to interact with business systems and workflows in a controlled, scalable way.
Engineer reliable backend services for agentic workloads, with emphasis on Python-based development and integration with Java service layers where required.
Implement and support production infrastructure for AI workloads, including environments where Kubernetes and model-serving components such as vLLM may be part of the stack.
Evaluate and communicate system failure modes, including the ability to walk through shipped systems, operational issues, debugging approaches, and mitigation strategies.
Collaborate with vendor, engineering, and business teams to deliver solutions with limited ramp-up time, consistent with expectations for senior contract engineering talent.
Maintain a production-first engineering standard, ensuring the role does not over-index on framework familiarity at the expense of real deployment experience.
Required Qualifications
7+ years of software engineering experience, with demonstrated experience building and shipping production systems.
Hands-on production experience with agentic AI or GenAI applications, including deployment, monitoring, debugging, and operating agents at scale.
Strong Python engineering skills, with the ability to work effectively in production AI and agentic system environments.
Java experience or willingness to work daily within a Java service layer, especially where enterprise systems require integration with existing backend services.
Experience with agent frameworks and orchestration technologies, including LangChain and/or LangGraph.
Familiarity with production infrastructure for AI systems, including Kubernetes-based deployment environments.
Ability to explain shipped system architecture and failure modes, including what was deployed, how it was monitored, where it failed, and how issues were resolved.
Comfort working in a senior contract delivery model where the expectation is faster delivery and limited ramp-up investment.
Preferred Qualifications
Experience with LangGraph as a production orchestration layer.
Experience with vLLM or comparable model-serving infrastructure.
Experience in regulated-industry or financial-services technology environments, especially where enterprise scale and production-path stakes are important.
Experience working with business stakeholders to deliver end-to-end AI use cases, not only platform or prototype work.
Ability to operate in an onsite or hybrid delivery model, especially in a market such as NYC where the attachment notes a deeper finance-AI contractor pool.
Engagement Expectations
Position the role as a senior contract role with a production-delivery bar, not as an entry-level GenAI experimentation role.
A 12-month engagement is reasonable for senior contractors, though onsite expectations may narrow the candidate pool.
If submissions are limited, relax requirements in this order: Java first, onsite days second, and do not relax the production-experience bar.
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